Methods and apparatus for compressing data streams. In an embodiment, a method includes calculating a decomposition of matrix data to generate eigenvectors and associated eigenvalues, determining clusters of the eigenvectors based on weighting the eigenvalues, calculating an eigenvector centroid for each cluster so that a dictionary of centroids is generated, and tagging the eigenvectors with tags, respectively, that identify an associated eigenvector centroid for each eigenvector. The method also includes counting a number of eigenvectors associated with each eigenvector centroid to construct a probability distribution function (PDF) of centroids, matching the PDF of centroids to PDF templates to determine a closest matching PDF template, determining an encoder corresponding to the closest matching PDF template wherein a corresponding encoder identifier is identified, encoding the tags with the encoder to generate an encoded data stream, and transmitting the encoded data stream, the encoder identifier, the dictionary of centroids, and the eigenvalues.

Methods and apparatus for compressing data streams. In an embodiment, a method includes calculating a decomposition of matrix data to generate eigenvectors and associated eigenvalues, determining clusters of the eigenvectors based on weighting the eigenvalues, calculating an eigenvector centroid for each cluster so that a dictionary of centroids is generated, and tagging the eigenvectors with tags, respectively, that identify an associated eigenvector centroid for each eigenvector. The method also includes counting a number of eigenvectors associated with each eigenvector centroid to construct a probability distribution function (PDF) of centroids, matching the PDF of centroids to PDF templates to determine a closest matching PDF template, determining an encoder corresponding to the closest matching PDF template wherein a corresponding encoder identifier is identified, encoding the tags with the encoder to generate an encoded data stream, and transmitting the encoded data stream, the encoder identifier, the dictionary of centroids, and the eigenvalues.

Herein are fine grained updates to pieces of JavaScript object notation (JSON) documents by database statements that can update, delete, and insert parts of JSON documents. In an embodiment, a computer receives a request that specifies a modification of a JSON document that is stored in a compressed format in persistent storage. The modification adds additional content to the JSON document, and/or replaces an old value in the JSON document with a new value that is not a same size as the old value. The modification is recorded in a change log. The change log is eventually applied to the compressed format of the JSON document in the persistent storage without entirely rewriting the compressed format of the JSON document in the persistent storage.

Herein are fine grained updates to pieces of JavaScript object notation (JSON) documents by database statements that can update, delete, and insert parts of JSON documents. In an embodiment, a computer receives a request that specifies a modification of a JSON document that is stored in a compressed format in persistent storage. The modification adds additional content to the JSON document, and/or replaces an old value in the JSON document with a new value that is not a same size as the old value. The modification is recorded in a change log. The change log is eventually applied to the compressed format of the JSON document in the persistent storage without entirely rewriting the compressed format of the JSON document in the persistent storage.

In various embodiments, an image encoding application determines a first value for an encoding parameter based on a search interval. The image encoding application then encodes a source image using the first value for the encoding parameter to generate a first encoded image. Subsequently, the image encoding application computes a visual quality score for a first reconstructed source image derived from the first encoded image. The image encoding application reduces the search interval based on a comparison between the visual quality score and the target visual quality score. Based on the resulting reduced search interval, the image encoding application determines a second value for the encoding parameter. The image encoding application encodes the source image using the second value for the encoding parameter to generate a second encoded image. Subsequently, the image encoding application transmits the second encoded image to software application(s) for further processing and display.

In various embodiments, an image encoding application determines a first value for an encoding parameter based on a search interval. The image encoding application then encodes a source image using the first value for the encoding parameter to generate a first encoded image. Subsequently, the image encoding application computes a visual quality score for a first reconstructed source image derived from the first encoded image. The image encoding application reduces the search interval based on a comparison between the visual quality score and the target visual quality score. Based on the resulting reduced search interval, the image encoding application determines a second value for the encoding parameter. The image encoding application encodes the source image using the second value for the encoding parameter to generate a second encoded image. Subsequently, the image encoding application transmits the second encoded image to software application(s) for further processing and display.

A collection of well-formed, but possibly semantically invalid, binary encoded multimedia data components or packages as well as the binary encoded announcement, signaling, and interchange protocols used in their transmission are converted into one or more well-formed extensible markup language (XML) files. Such XML files may then be validated according to one or more pre-defined XML schemas, or similar schema languages, in order to verify that the data and protocol structures and substructures adhere to prior defined semantic constraints.

A collection of well-formed, but possibly semantically invalid, binary encoded multimedia data components or packages as well as the binary encoded announcement, signaling, and interchange protocols used in their transmission are converted into one or more well-formed extensible markup language (XML) files. Such XML files may then be validated according to one or more pre-defined XML schemas, or similar schema languages, in order to verify that the data and protocol structures and substructures adhere to prior defined semantic constraints.

An encoding apparatus includes a memory and a processor configured to acquire text data, specify a first dynamic dictionary among a plurality of dynamic dictionaries based on attribute information of a first word included in the text data, register the first word in association with a first dynamic code in the first dynamic dictionary, and encode the first word into the first dynamic code.

An encoding apparatus includes a memory and a processor configured to acquire text data, specify a first dynamic dictionary among a plurality of dynamic dictionaries based on attribute information of a first word included in the text data, register the first word in association with a first dynamic code in the first dynamic dictionary, and encode the first word into the first dynamic code.